—We propose an approach for improving object recognition and localization using spatial kernels together with instance embedding. Our approach treats each image as a bag of insta...
Kernel descriptors provide a unified way to generate rich visual feature sets by turning pixel attributes into patch-level features, and yield impressive results on many object rec...
Liefeng Bo, Kevin Lai, Xiaofeng Ren and Dieter Fox
In this paper, a kernel-based method for multi-object retrieval in large image database is presented. First, our approach exploits a fuzzy region segmentation approach in order to...
Philippe Henri Gosselin, Matthieu Cord, Sylvie Phi...
We propose a novel privacy-preserving nonlinear support vector machine (SVM) classifier for a data matrix A whose columns represent input space features and whose individual rows ...
In this paper we present the face recognition method using feature-level fusion where the infrared (IR) and visible face images are fused at transformed domain. The main contribut...